Acceptance of Electronic Tax Filing System (Literature Review)

Topics: Taxation in the United States, Tax, Psychology Pages: 2 (551 words) Published: September 12, 2013
Acceptance of Electronic Tax Filing System


Governments around the world are started relying on e-government system such as e-filing system to improve their efficiency and effectiveness in tax return. The number of literatures is getting more on e-filing system. According to Azmi and Bee (2010), Azmi et al. (2012), Fu et al. (2006), Schaupp et al. (2010) and Suhani Anuar and Radiah Othman (2010), they assessed the acceptance intention of the e-filing system by using Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). In the previous literatures, the determinants of e-filing tax system in the TAM which widely used are perceived usefulness and perceived ease of use. Besides the technology adoption determinants, perceived risk is also an important prediction that used to examine the attitude of taxpayers toward e-filing tax system. In the five existing literatures and studies, perceived usefulness, perceived ease of use and perceived risk are the determinants of variables which used to measure and examine the intention of use or behavioral intention. Perceived usefulness is defined as the user’s perception of the probability of using a system will increase his or her job performance and perceived ease of use is defined as the perception of the degree of effort the user needs to use the system (Azmi and Bee, 2010; Fu et al., 2006). Perceived risk is defined as the perception of the amount of loss or uncertainty that a user will encounter while pursuing a desired outcome (Ng and Bee. 2010; Fu et al, 2006; Schaupp et al., 2010). From the mentioned literature, the other factors which used to examine the intention to use included subjective norms/social influence (Fu et al., 2006; Schaupp et al., 2010), self-efficacy (Fu et al, 2006), facilitating conditions (Fu et al., 2006; Schaupp et al., 2010; Suhani Anuar and Radiah Othman, 2010), amount of information (Suhani Anuar and Radiah Othman, 2010) and optimism bias...
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